Dew-Cloud-Based Hierarchical Federated Learning for Intrusion Detection in IoMT.

The coronavirus pandemic has overburdened medical institutions, forcing physicians to diagnose and treat their patients remotely. Moreover, COVID-19 has made humans more conscious about their health, resulting in the extensive purchase of IoT-enabled medical devices. The rapid boom in the market worth of the internet of medical things (IoMT) captured cyber attackers' attention. Like health, medical data is also sensitive and worth a lot on the dark web. Despite the fact that the patient's health details have not been protected appropriately, letting the trespassers exploit them. The system administrator is unable to fortify security measures due to the limited storage capacity and computation power of the resource-constrained network devices'. Although various supervised and unsupervised machine learning algorithms have been developed to identify anomalies, the primary undertaking is to explore the swift progressing malicious attacks before they deteriorate the wellness system's integrity. In this paper, a Dew-Cloud based model is designed to enable hierarchical federated learning (HFL). The proposed Dew-Cloud model provides a higher level of data privacy with greater availability of IoMT critical application(s). The hierarchical long-term memory (HLSTM) model is deployed at distributed Dew servers with a backend supported by cloud computing. Data pre-processing feature helps the proposed model achieve high training accuracy (99.31%) with minimum training loss (0.034). The experiment results demonstrate that the proposed HFL-HLSTM model is superior to existing schemes in terms of performance metrics such as accuracy, precision, recall, and f-score.

Transparent CoAP Services to IoT Endpoints through ICN Operator Networks.

The Constrained Application Protocol (CoAP) is a specialized web transfer protocol which is intended to be used for constrained networks and devices. CoAP and its extensions (e.g., CoAP observe and group communication) provide the potential for developing novel applications in the Internet-of-Things (IoT). However, a full-fledged CoAP-based application may require significant computing capability, power, and storage capacity in IoT devices. To address these challenges, we present the design, implementation, and experimentation with the CoAP handler which provides transparent CoAP services through the ICN core network. In addition, we demonstrate how the CoAP traffic over an ICN network can unleash the full potential of the CoAP, shifting both overhead and complexity from the (constrained) endpoints to the ICN network. The experiments prove that the CoAP Handler helps to decrease the required computation complexity, communication overhead, and state management of the CoAP server.

Controller⁻Pilot Data Link Communication Security.

The increased utilization of the new types of cockpit communications, including controller⁻pilot data link communications (CPDLC), puts the airplane at higher risk of hacking or interference than ever before. We review the technological characteristics and properties of the CPDLC and construct the corresponding threat model. Based on the limitations imposed by the system parameters, we propose several solutions for the improved security of the data messaging communication used in air traffic management (ATM). We discuss the applicability of elliptical curve cryptography (ECC), protected aircraft communications addressing and reporting systems (PACARs) and the Host Identity Protocol (HIP) as possible countermeasures to the identified security threats. In addition, we consider identity-defined networking (IDN) as an example of a genuine security solution which implies global changes in the whole air traffic communication system.

Secure and Efficient Reactive Video Surveillance for Patient Monitoring.

Video surveillance is widely deployed for many kinds of monitoring applications in healthcare and assisted living systems. Security and privacy are two promising factors that align the quality and validity of video surveillance systems with the caliber of patient monitoring applications. In this paper, we propose a symmetric key-based security framework for the reactive video surveillance of patients based on the inputs coming from data measured by a wireless body area network attached to the human body. Only authenticated patients are able to activate the video cameras, whereas the patient and authorized people can consult the video data. User and location privacy are at each moment guaranteed for the patient. A tradeoff between security and quality of service is defined in order to ensure that the surveillance system gets activated even in emergency situations. In addition, the solution includes resistance against tampering with the device on the patient's side.

An efficient and adaptive mutual authentication framework for heterogeneous wireless sensor network-based applications.

Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications.